1. Cross Reference to Related Application
This application is related to Application, Ser. No. 08/955,773, filed on the filing date of this application, entitled AUTOMATIC DEFECT RECLASSIFICATION OF IDENTIFIED PROPAGATOR DEFECTS and is assigned to the assignee of this application.
2. Field of the Invention
This invention relates generally to a defect classification methodology in a semiconductor manufacturing testing system and more specifically, to an automatic defect classification methodology that reclassifies propagator defects using data obtained in a current layer and classifies at least one defect from each cluster.
3. Discussion of the Related Art
In order to remain competitive, a semiconductor manufacturer must continuously increase the performance of the semiconductor integrated circuits being manufactured and at the same time, reduce the cost of the semiconductor integrated circuits. Part of the increase in performance and the reduction in cost of the semiconductor integrated circuits is accomplished by shrinking the device dimensions and by increasing the number of circuits per unit area on an integrated circuit chip. Another part of reducing the cost of a semiconductor chip is to increase the yield. As is known in the semiconductor manufacturing art, the yield of chips (also known as die) from each wafer is not 100% because of defects during the manufacturing process. The number of good chips obtained from a wafer determines the yield. As can be appreciated, chips that must be discarded because of a defect or defects increases the cost of the remaining usable chips.
A single semiconductor chip can require numerous process steps such as oxidation, etching, metallization and wet chemical cleaning. Some of these process steps involve placing the wafer on which the semiconductor chips are being manufactured into different tools during the manufacturing process. The optimization of each of these process steps requires an understanding of a variety of chemical reactions and physical processes in order to produce high performance, high yield circuits. The ability to view and characterize the surface and interface layers of a semiconductor chip in terms of their morphology, chemical composition and distribution is an invaluable aid to those involved in research and development, process, problem solving, and failure analysis of integrated circuits.
Although it would be desirable to be able to identify and analyze each defect on each wafer in every manufacturing run it is not practical. In practice, a particular lot (a number of wafers) is selected to be representative of the manufacturing run. At least one wafer is selected from the lot to be analyzed. Because of the number of processes, it may not be possible to re-analyze each wafer after each process. Therefore, only certain processes may be selected to be analyzed. After each process that has been selected to be analyzed, the wafer is placed in an inspection tool that detects defects. As can be appreciated, there may be more defects than can be practically analyzed.
In the field of in-line defect detection and analysis there is a three-pronged focus of effort to try to explain the past (what has happened to the wafer), the present (what is happening to the wafer), and the future (what will happen to the wafer). Because of the number of defects that must be analyzed or accounted for, techniques have been developed to assist in the practical analysis of defects. One technique is called partitioning which is a technique where defects from the current layer of the wafer are mapped against defects from previous layers of the same wafer. Any defect from the current layer found within a certain radius of any previous layer defect is marked as a previous layer defect. The rationale for this is that the defects within a certain radius are the same defect. Because of this probability, only one of the previous layer defects within the selected radius is selected to be analyzed because to analyze further defects within the selected radius would be a waste of resources, time, and effort. The technique of partitioning separates previous layer defects from current layer defects, which are called "adders" and which are therefore eligible to be selected to be analyzed with the other defects in the current layer. Another technique to assist in the analysis of defects is the technique of declustering. Declustering is a technique in which all defects within a certain radius of each other are treated as a single defect, since it is probable that they were caused by the same event, such as a scratch, patch of residue, etc.
Presently, there is no method by which a detected defect in the present layer can be identified as a propagator and further, if it is a propagator, whether it will be a killer (die destructive) defect. Without such a method, a defect that may be a killer defect may be considered to be a benign defect. The early and proper classification and/or reclassification of possible killer defects is critical for any models or simulators, which will subsequently use this data for predicting or forecasting yields. In addition, it will place knowledge relating to the potential destructive nature of the defect in the hands of the process engineer so an intelligent decision can be made whether to scrap or send on wafers when dispositioning lots. In the present methodology, once a defect is classified, the defect is not reclassified and therefore, information concerning the characteristics of that defect in subsequent layers is not obtained. This information would be invaluable for the development of models that would predict at an early stage not only that a defect is a propagator defect but that the defect is going to be a killer defect. In addition, when a defect is characterized as a cluster defect all of the defects within that cluster are placed in the sample population. Therefore, the probability of one of the cluster defects being chosen to be classified depends upon the total number of defects that are detected on that particular layer.
Therefore, what is needed is a method to determine whether a defect is a propagator, whether it has been previously classified, and to reclassify the propagator defect. In addition, what is needed is a method to add at least one cluster defect to the number of defects that will be classified.